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Electric Vehicles are rapidly growing in the market yet various doubts on success of its adaptation were noted all along the globe. On the question part range is one of the major attribute; however, range anxiety has greatly inspired manufacturers to explore new practices to improve. One of the most important components of an electric vehicles (EV) is the battery, which converts chemical energy to electrical energy thereby liberating heat energy as the loss. When this heat energy loss is high, the energy available in the battery for propulsion is reduced significantly. Additionally, with a higher heat loss in the battery, system is prone to failure or reduced mileage. Therefore, controlling/maintaining system temperature under safe usable limits even during harsh conditions is critical. Simple reduction in energy consumption of electrical cooling/heating devices used with regenerative energy techniques can greatly help in range improvement.

Electric car markets experience exponential growth. As per IEA battery electric vehicles sales exceeded 10 million in 2022 [1] . There is projection from IEA that EV sales will touch 40 million mark by 2030, major contribution from China (12 m) and Europe (13.3 m) regions [2]. This growth projection attributed to many global factors, government policies, automakers commitment, climate change, etc. There is a massive push from global institutions and automobile community for transition to electric mobility. There is a 66% likelihood that the annual average near-surface global temperature between 2023 and 2027 will be more than 1.5°C above pre-industrial levels for at least one year. There is a 98% likelihood that at least one of the next five years, and the five-year period, will be the warmest on record [3]. Hence transition is imperative to reduce greenhouse gases and adhere to climate change commitments. Today EVs are not popular as ICE.

With advancement and increase in usage of Li-ion batteries in sectors such as electronic equipment’s, Electric Vehicles etc battery lifetime is critical for estimation of product life. It is well known that temperature and voltage strongly influence the degradation of lithium-ion batteries and that it depends on the chemical composition and structure of the positive and negative electrodes. Lithium batteries are continuously subjected to various load cycles and ambient temperatures depending on application of battery. Thus, in many applications Cycle aging could be the main contributor or factor for battery degradation, thus reduction in life of product. Thus, there is strong need for researchers and engineers to help improve life of cells or batteries being used in electric vehicles. In this present work, cycle aging of commercial 18650 cell is studied at ambient temperature. Experimental data shows that about nearly 20 % cell capacity degrades at ambient temperature.

Pulse Width Modulation or PWM has been widely used in traction motor control for electric propulsion systems. The associated switching noise has become one of the major NVH concerns of electric vehicles (EVs). This paper presents a multi-disciplinary study to analyze and validate current ripple induced switching noise for EV applications. First, the root cause of the switching noise is identified as high frequency ripple components superimposed on the sinusoidal three-phase current waveforms, due to PWM switching. Measured phase currents correlate well with predictions based on an analytical method. Next, the realistic ripple currents are utilized to predict the electro-magnetic dynamic forces at both the motor pole pass orders and the switching frequency plus its harmonics. Special care is taken to ensure sufficient time step resolution to capture the ripple forces at varying motor speeds.

The world is moving towards E-mobility solutions and Battery Electric Vehicles (BEVs) are the main enabler towards it. Li-ion cells are the fundamental building block of any BEVs. There are three common types of Li-ion cell design i.e., cylindrical cells, Prismatic Cells and Pouch cells. Ensuring safety of BEVs are critical to gain customer trust and acceptance over Internal Combustion Engine (ICE) vehicles. EV fire is found to be one of the major concerns related to using higher energy batteries. During a crash event, Post-Crash Electrical Integrity of the BEV is to be ensured and hence primary focus is on mitigation of Li-ion cell internal short circuit. It has been seen in prior published articles that cell internal short circuit can be triggered by physical intrusion of cell. This paper primarily focusses on simulating the mechanical behavior of cylindrical cell under various crush conditions.

Battery Electric Vehicles (BEVs) are becoming more competitive day by day to achieve maximum peak power and energy requirement. This poses challenges to the design of Thermal Interface Material (TIM) which maintains the cell temperature and ensure retention of cell and prevent electrolyte leak under different crash loads. TIM can be in the form of adhesives, gels, gap fillers. In this paper, TIM is considered as structural, and requires design balance with respect to thermal and mechanical requirements. Improving structural strength of TIM will have negative impact on its thermal conductivity; hence due care needs to be taken to determine optimal strength that meets both structural and thermal performance. During various crash conditions, due to large inertial force of cell and module assembly, TIM is undertaking significant loads on tensile and shear directions. LS-DYNA® is used as simulation solver for performing crash loading conditions and evaluate structural integrity of TIM.

As the world is moving towards greener energy solutions, there is a clear transition seen from ICE to EV powertrain solution. The cost of vehicle is primarily controlled by battery pack as it is high capital intense. Though Li-Ion battery is a very promising technology in terms of energy storage and long-term performance, safety of battery is a concern. Battery can undergo self-fire/ thermal runaway due to several factors like aging, internal short, overcharging etc. A numerical investigation is carried out for a conceptual 10S1P prismatic battery pack to model the nail penetration using commercial ANSYS Fluent tool. Vent gas generation has been modelled and its convective effects on Thermal runaway were studied. Vent gas generation is supported through a user defined function which calculates the amount of flow rate that vent gas encounters during thermal runaway.

Numerical simulation of lithium-ion batteries (LIB) has become extremely vital in the understanding of thermal behaviour of LIBs to develop active and passive battery thermal management systems. The LIB is popular in consumer electronics. Beyond consumer electronics, the LIB is also growing in popularity for the automotive applications such as hybrid electric vehicles (HEVs) and battery electric vehicles (BEVs) due to its high energy density, high voltage, and low self-discharge rate. High amount of heat generally gets developed during charge and discharge of LIB based on the c-rate at which it is being discharged or charged. Hence, there should be a mechanism to understand the thermal behaviour of these cells. Thus, in this paper a numerical procedure has been developed to model electrochemical-thermal behaviour of commercially available 21700 Li-ion cells. NewmanP2D approach is used to arrive at electrochemistry performance of Li-ion cell and pack.

Oven exposure testing is a standard benchmark (where Li-ion cells are exposed to higher temperature) that Li-ion cells must pass to get approval for sale by the regulating bodies. These tests are designed to ensure the safety of battery user as the Li-ion batteries are vulnerable to abuse conditions. However, these tests can be both costly and time consuming. Hence, development of simulation capabilities which can replace the physical test to a certain extent helps both battery manufacturers and OEMs not only in the cost cutting but also to optimize the critical parameters which can directly influence the safety criterions. In this paper, a numerical model of 18650 NCM Li-ion cell in an oven test condition is developed to study the thermal runaway, cell venting, internal pressure buildup, and gas flow behavior using ANSYS FLUENT commercial software.

High energy and power density Lithium-ion batteries are used as energy storage devices for indispensable applications ranging from cell phones to hybrid electric vehicles, unmanned aerial vehicles and commercial passenger aircrafts. To monitor the health of the battery and its various performances, it is crucial to understand the electrochemical behavior of the battery. The Doyle-Fuller-Newman (DFN) model is a popular electro-chemistry-based model, which characterizes the solid and electrolyte diffusion dynamics in the battery and predicts current/voltage response. However, the DFN model requires many parameters that need to be estimated to obtain an accurate battery model. In this article, an electro-chemistry based cell model is developed using GT-AutoLion to simulate and validate the performance for two different commercially available Lithium Iron Phosphate (LiFePO4) and Nickel Cobalt Aluminum (NCA) cells.

Hyper-elastic seals are extensively used in automotive applications for sealing various joints in assembly. They are also used in sealing battery packs. They are used in various sizes and shapes. Most of the gaskets used are solid gaskets. Hollow gaskets are also being used. Hollow gaskets typically have a fluid like air trapped inside. Analyzing these hollow gaskets also requires involving the physics of the fluid inside. The trapped fluid affects the performance of the gasket like contact pressure and width. Objective of this study is to analyze the hollow gasket performance including the effect of air trapped inside. The effect of air on performance of the hollow seal is also studied. Fluid Cavity capability in ABAQUS was selected after literature study to simulate the effect of trapped fluid (Air) on seal performance.

The battery cell unit and battery module constitute the building blocks for the battery pack in an electric vehicle. It is important to rigorously understand the vibration induced response of the battery pack as it is a prerequisite for the safety of an electric vehicle. An accurate finite element (FE) model plays a key role in predicting the dynamic response of the battery pack simulation. In this paper, finite element analysis (FEA) results are compared with the experimental set up of the battery components and a 60-cell battery module. Using orthotropic elastic constants instead of isotropic properties to model the fiber reinforced polymer (FRP) made battery components produced better modal results correlation. Modal frequency values for the brick components have been improved by 25% to 50%. For the battery module, swapping of mode shape behavior is observed between finite element model and experimental results.

Gasoline Particulate Filters (GPF) are widely employed in exhaust aftertreatment systems of gasoline engines to meet the stringent particulate emissions requirements of Euro 6 and China 6 standard. Optimization of GPF performance requires a delicate trade-off between fuel economy, engine performance and drivability. This results in a complex lengthy and iterative calibration development process which uses a lot of hardware resources. To improve the calibration process and reduce hardware testing, physics-based modeling of the GPF system is used. A 1-D chemical model supplemented with 3D CFD solver is utilized to evaluate pressure drop and soot burning performance characteristics of the GPF under engine dynamometer test conditions. The chemical kinetics of soot burning for the 1D model is developed using test data obtained from well controlled laboratory environment.

Traction Control System (TRCS) has become a standard feature for most of the vehicles due to safety considerations. The system provides better drivability and acceleration performance on low friction surfaces. The TRCS typically tries to maintain slip value to an optimum value to maximize traction force by modifying engine torque and/or brake force intervention. However the optimum slip value is not a constant value and varies depending upon the road surface and tyre conditions. It is challenging task to predict this value dynamically and adapt TRCS under all driving situation. This paper presents an adaptive traction control system which tries to operate at optimum slip point irrespective of prior knowledge of road condition. The system continuously monitors vehicle dynamics parameters and corrects itself to maximize available traction. The controller has been developed using Matlab Simulink platform.

For engine diagnostics and fault-tolerant control system design provision of analytical models, in the form of virtual sensors, will enable more reliable system design and operation. This paper presents applications of recurrent neural network (RNN)-based architectures for the development of virtual sensors for salient SI engine variables such as manifold absolute pressure, mass airflow rate, air-fuel ratio and engine torque. The RNN architectures developed allow effective sensing of these crucial engine variables while, for computational efficiency, keeping a compact size for the network topology. A nonlinear state-space model strategy is proposed for architecting the stated recurrent neural network and is trained using variants of the real-time recurrent learning (RTRL) algorithm. Representative experimental results obtained for a 5.7 L V8 engine are listed and discussed. The application, dependency and limitations of the proposed approaches are also pointed out.